Drone-Sharing Models for Inclusive Precision Agriculture

Sofia Moretti

Drone-Sharing Models for Inclusive Precision Agriculture

Author(s)	Dr. Sofia Moretti
Country	United States
Abstract	Unmanned aerial vehicles have expanded the technical possibilities of precision agriculture by enabling high-resolution crop monitoring, stress detection, field mapping, spraying, and other spatially targeted operations. Their benefits, however, can remain concentrated among larger or better-capitalized farms when access depends on individual ownership of aircraft, sensors, software, trained operators, and data-processing infrastructure. This study develops a simulation-based framework for evaluating drone-sharing models as mechanisms for more inclusive precision agriculture. Five access arrangements are compared: individual ownership, peer-to-peer rental, cooperative sharing, custom hiring centers, and drone-as-a-service provision. An Inclusive Drone Access Index is constructed using affordability, operational timeliness, technical-service capacity, farmer inclusion, and data-governance quality. The simulated index increases from 50.4 under individual ownership to 58.1 for peer rental, 75.8 for cooperative sharing, 82.9 for custom hiring centers, and 88.3 for drone-as-a-service. The analysis indicates that sharing can reduce the fixed-cost barrier to precision agriculture, but affordability alone does not guarantee inclusion. Seasonal service congestion, operator shortages, inaccessible digital interfaces, weak agronomic interpretation, uncertain data rights, and exclusion of remote or very small farms can reproduce inequality even under nominally shared systems. Cooperative and custom-hiring arrangements offer stronger potential when booking rules, pricing, service territories, operator training, and data responsibilities are transparent. Drone-as-a-service performs most strongly in the simulation because specialized equipment, operators, maintenance, analytics, and farmer-facing interpretation can be combined within one service relationship. The study concludes that drone sharing should be designed as an inclusive agricultural service system rather than simply as equipment rental. Effective models require farmer-oriented scheduling, transparent pricing, locally available operators, interoperable data, accountable data governance, and deliberate safeguards for small and resource-constrained producers.
Keywords	agricultural drones, precision agriculture, drone sharing, smallholder farming, custom hiring, digital agriculture, technology inclusion, drone-as-a-service
Field	Engineering
Published In	Volume 7, Issue 1, January-February 2026
Published On	2026-02-04

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American Journal of Advanced Multidisciplinary Innovation and Research

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Drone-Sharing Models for Inclusive Precision Agriculture

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